Zhenyuan Wang

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About

Zhenyuan Wang is a leading researcher at the intersection of human-robot interaction, organizational behavior, and technology acceptance. Their work critically examines how robotic transparency and anthropomorphism shape employee trust and acceptance of automation in the workplace. Wang’s most-cited study, "Robot Transparency and Employees’ Acceptance: The Roles of Trust and Anthropomorphism" (2025), has already garnered 4 citations, signaling its early impact in a rapidly evolving field. By empirically demonstrating that transparent robotic behaviors—such as explaining actions or displaying intent—enhance trust and reduce resistance, Wang provides actionable insights for designing collaborative robots that integrate seamlessly into human-centered work environments. This contribution is particularly vital as organizations increasingly deploy AI and robotics alongside human teams. Wang’s research bridges engineering, psychology, and management, offering a nuanced understanding of how social cues in machines influence human perceptions and adoption. Their work not only advances theoretical frameworks in technology acceptance but also informs practical strategies for ethical and effective automation. As the field grows, Wang’s findings will remain essential for researchers and practitioners seeking to foster harmonious human-robot collaboration.